ACM poster 2017

Intro

In this report we are focusing on the most frequented edges, all having more than 170 sessions along April 2016. All of this edges are around FEUP.

The data frame to use is: df_superhotedges_april16pt. It was created with the df df_speed_top which brings directly all points of the top edges from the database. The following filters were applied (more info: PreAnalysis_topedges.Rmd) Week days Hour between 8hr and 20h

Given a total of 9 variables, 9 edges, 1369 sessions and 190201 points. 
Half of the the sessions involve just one edge.  
1011 pass by Frei
150 sessions have gaps over 5min 
394 sessions have gaps over 2min 

Map with number of sessions

ms_3 <- m 
ms_3

Intersession time

Interpoint time

df_superhotedges_april16pt %>% 
  group_by(session_id) %>% 
  summarise(n = n_distinct(session_id))
  

  filter(way_id != 37141967) %>% 
  fgroup_by(session_id) %>% 
  summarise(speed = quantile(speed,0.9)) %>% 
  filter(speed == 0)

Temporal

df_sessions_allmodes %>% 
  filter(travelmode != "NA") %>% 
  group_by(hour = hour(time_start), travelmode) %>% 
  summarise(n_sessions = n_distinct(session_id)) %>% 
  ggplot(aes(x = hour,y = n_sessions, color=travelmode)) +
  geom_line() + 
  scale_x_continuous(breaks = seq(0,23,1)) + 
  theme_light()

Origin-Destination

External Factors(parking, etc)

df_superhotedges_april16pt %>% 
  filter((way_id == 37141967 & session_id == 47192))  %>% 
  plot_ly( x= ~time, y= ~track,color = ~factor(segment_id), type ="scatter")

No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode

Frei

Manuel Silva

df_superhotedges_april16pt %>% 
  filter(way_id == 35078500 & session_id == 19802)  %>% 
  plot_ly( x= ~time, y= ~speed,color = ~factor(way_id), type ="scatter", mode ="lines") 

minimal value for n is 3, returning requested palette with 3 different levels
minimal value for n is 3, returning requested palette with 3 different levels

Density

Rascunhos

df_superhotedges_april16pt %>% 
  filter((way_id == 37141967 & session_id == 47419))  %>% 
  plot_ly( x= ~time, y= ~track,color = ~factor(segment_id), type ="scatter")

No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode

df_superhotedges_april16pt %>% 
  filter(( session_id == 14249))  %>% 
  plot_ly( x= ~time, y= ~speed,color = ~factor(way_id), type ="scatter") 

No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
minimal value for n is 3, returning requested palette with 3 different levels
No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
minimal value for n is 3, returning requested palette with 3 different levels

df_hotedges_april16pt %>% 
  group_by(session_id) %>% 
  summarise(n = n_distinct(way_id)) %>% 
  filter(n > 5) %>% 
  arrange((n))

f <- df_edges_april16pt %>% 
  filter(session_id == 35307)


write.csv(f,"f.csv")